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The Changing Economic Preferences of the American Public: 1976-1991 Sekhon, Jasjeet Uploaded 03-28-1997 Keywords Macroeconomic Preferences Monetary Policy Hermite Polynomials Splines Bootstrap Abstract I show that the public indeed does have coherent preferences over macroeconomic tradeoffs, and these preferences have changed in ways consistent with not only economic theory but also with the changes which occurred in the American political system during the 1980s. In particular, most people learned something new about the state of the world in the late 1970s, and began to reject classical Keynesian explanations about economic reality. Individuals were becoming more sympathetic to the economic platform of the Republican party---i.e., they began to favour price stability. Moreover, the results support the notion that poor Americans do not hold government policy responsible for their personal economic plight (Hochschild 1981, Lane 1962).

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Getting the Mean Right is a Good Thing: Generalized Additive Models Beck, Nathaniel Jackman, Simon Uploaded 01-30-1997 Keywords non-parametric regression scatterplot smoothing local fitting splines non-linearity Perot incumbency cabinet duration democratic peace Abstract This is a substantial revision of the paper submitted as beck96. A shorter version of this paper is under consideration at a political science journal of note. Theory: Social scientists almost always use statistical models positing the dependent variable as a linear function of X, despite suspicions that the social and political world is not so parsimonious. Generalized additive models (GAMs) permit each independent variable to be modelled non-parametrically while requiring that the independent variables combine additively, striking a sensible balance between the flexibility of non-parametric techniques and the ease of interpretation and familiarity of linear regression. GAMs thus offer social scientists a practical methodology for improving on the extant practice of ``linearity by default''. Method: We present the statistical concepts and tools underlying GAMs (e.g., scatterplot smoothing, non-parametrics more generally, and accompanying graphical methods), and summarize issues pertaining to estimation, inference, and the statistical properties of GAMs. Monte Carlo experiments assess the validity of tests of linearity accompanying GAMs. Re-analysis of published work in American politics, comparative politics, and international relations demonstrates the usefulness of GAMs in social science settings. Results: Our re-analyses of published work show that GAMs can extract substantive mileage beyond that yielded by linear regression, offering novel insights, particularly in terms of modelling interactions. The Monte Carlo experiments show there is little danger of GAMs spuriously finding non-linear structures. All data analysis, Monte Carlo experiments, and statistical graphs were generated using S-PLUS, Version 3.3. The routines and data are available at ftp://weber.uscd.edu/pub/nbeck/gam.

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Covariate Functional Form in Cox Models Keele, Luke Uploaded 10-25-2005 Keywords Cox model event history survival models splines semi-parametric duration models Abstract In most event history models, the effect of a covariate on the hazard is assumed to have a log-linear functional form. For continuous covariates, this assumption is often violated as the effect is highly nonlinear. Assuming a log-linear functional form when the nonlinear form applies causes specification errors leading to erroneous statistical conclusions. Scholars can, instead of ignoring the presence of nonlinear effects, test for such nonlinearity and incorporate it into the model. I review methods to test for and model nonlinear functional forms for covariates in the Cox model. Testing for such nonlinear effects is important since such nonlinearity can appear as nonproportional hazards, but time varying terms will not correct the misspecification. I investigate the consequences of nonlinear function forms using data on international conflicts from 1950-1985. I demonstrate that the conclusions drawn from this data depend on fitting the correct functional form for the covariates.